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Title: Data Engineer IV
Location: Cincinnati, OH
Duration: 12 Months with possible extensions
Technical Skills:
Must Have: ETL, Python, SQL
Nice To Have: , ,
JOB DESCRIPTION: Squad: Machine Learning Data Enablement squad in the Data Insights Tribe
Required: In office 4 days a week minimum (Monday Thursday)
We re hiring a Data Engineer to join our newly launched Machine Learning Data Enablement team at Fifth Third Bank. This team is focused on building high-quality, scalable data pipelines that power machine learning models across the enterprise, deployed in AWS SageMaker.
We re looking for an early-career professional who s excited to grow in a hands-on data engineering role. Ideal candidates will have experience working on machine learning related projects or have partnered with data science teams to support model development and deployment and have a strong interest in enabling ML workflows through robust data infrastructure.
You ll work closely with data scientists and ML engineers to deliver curated, production-ready datasets and help shape how machine learning data is delivered across the bank. You should have solid SQL and Python skills, a collaborative mindset, and a strong interest in modern data tooling. Experience with Snowflake, dbt, or cloud data platforms is a strong plus. Familiarity with ML tools like SageMaker or Databricks is helpful but not required we re happy to help you learn.
This is a hands-on role with high visibility and high impact. You ll be joining a team at the ground level, helping to define how data powers machine learning at scale.
Title: Data Engineer IV
Location: Cincinnati, OH
Duration: 12 Months with possible extensions
Technical Skills:
Must Have: ETL, Python, SQL
Nice To Have: , ,
JOB DESCRIPTION: Squad: Machine Learning Data Enablement squad in the Data Insights Tribe
Required: In office 4 days a week minimum (Monday Thursday)
We re hiring a Data Engineer to join our newly launched Machine Learning Data Enablement team at Fifth Third Bank. This team is focused on building high-quality, scalable data pipelines that power machine learning models across the enterprise, deployed in AWS SageMaker.
We re looking for an early-career professional who s excited to grow in a hands-on data engineering role. Ideal candidates will have experience working on machine learning related projects or have partnered with data science teams to support model development and deployment and have a strong interest in enabling ML workflows through robust data infrastructure.
You ll work closely with data scientists and ML engineers to deliver curated, production-ready datasets and help shape how machine learning data is delivered across the bank. You should have solid SQL and Python skills, a collaborative mindset, and a strong interest in modern data tooling. Experience with Snowflake, dbt, or cloud data platforms is a strong plus. Familiarity with ML tools like SageMaker or Databricks is helpful but not required we re happy to help you learn.
This is a hands-on role with high visibility and high impact. You ll be joining a team at the ground level, helping to define how data powers machine learning at scale.